The latest pullback in AI equities has triggered sharp debate across markets, with skeptics pointing to Nvidia’s $100 billion partnership with OpenAI as evidence of a “closed cycle” of money and hype. The narrative is simple: Nvidia helps finance OpenAI, OpenAI spends billions on Nvidia’s GPUs, and the money effectively recirculates to sustain inflated valuations. For three days running, AI-linked stocks have stumbled on this notion, with critics suggesting the entire sector is showing classic bubble dynamics. But this argument, while catchy, falls apart under closer scrutiny.
First, the idea of a perfectly closed loop ignores the breadth of AI’s ecosystem. OpenAI and other frontier labs are not funneling every dollar back into Nvidia. Their capital is spread across data center infrastructure, networking, energy, software engineering, cloud deployment, and vertical applications in sectors from healthcare to finance. Nvidia is a central player, but far from the only beneficiary. The AI economy is not a two-party circle—it’s a rapidly expanding supply chain touching dozens of industries.
Second, real demand for compute is surging, not just imagined. Training and running multimodal foundation models requires exponential increases in processing power. Each new generation of models consumes more compute than the last, and inference workloads are growing even faster than training. Here, the Jevons paradox is instructive: as compute becomes more powerful and efficient, total consumption tends to rise rather than fall. This dynamic explains why cloud hyperscalers, enterprises, and governments continue to scale AI spending despite cost pressures.
Third, the true risk is not the existence of a closed financial cycle, but valuation misalignment. Investors often price companies today based on expected future capabilities that may not yet exist. If those expectations are delayed by regulation, bottlenecks, or competitive pressure, the stocks tied to them can deflate quickly. Nvidia’s OpenAI deal highlights this tension. While some analysts see it as “circular vendor financing,” others see it as a way of securing long-term demand and ensuring capacity for future breakthroughs. Both interpretations carry truth, but neither justifies dismissing the entire AI sector as a bubble.
Fourth, there are legitimate antitrust and competition concerns. With Nvidia dominating the AI chip market, regulators are scrutinizing whether its deep entanglement with OpenAI could tilt the playing field against rivals. These challenges could weigh on sentiment in the near term. Yet paradoxically, regulatory focus is also a sign of how central and indispensable AI has already become to national competitiveness and economic growth.
Finally, the recent three-day slump is more a signal of sentiment fragility than structural collapse. Periodic corrections are normal in disruptive technology cycles, especially when valuations stretch into uncharted territory. But major institutions remain committed: capital expenditures on AI infrastructure by hyperscalers continue to accelerate, governments are funding sovereign AI initiatives, and enterprises are embedding AI into workflows at a pace unseen since the rise of the internet. Wells Fargo’s strategists recently argued that despite froth in some areas, AI remains an enduring growth story with transformative impact across industries.
The “closed cycle” critique makes for an attractive headline, but it oversimplifies a far more complex and durable transformation. AI is not merely an internal loop between Nvidia and OpenAI; it is a broad technological wave reshaping compute, productivity, and national strategy. While valuations may need recalibration and some players could falter, the sector itself is not in a hollow bubble—it is in the early innings of industrial-scale adoption.
